Empirical Model for Predicting Process Parameters during Electric Arc Furnace Refining Stage Based on Real Measurements

Abstract

The present study aims at building a road map‐model for the steel melt compositional variations during the electric arc furnace (EAF) refining stage. The model is based on real measurements and compared to thermodynamic predictions. The studied parameters are steel melt carbon content and temperature. Herein, high‐temperature investigations (1550–1700 °C) with different chemistry ranges (mainly carbon content, 0.02–0.20% C) are carried out during the refining stage operation. The work develops a detailed empirical model to simulate the industrial EAF refining stage, which can be used to implement different optimization and control strategies for the EAF refining process. Furthermore, the study investigates the refining stage metallurgical phenomenon and the different operating conditions used to produce different steel grades over a wide range of carbon content; from ultra‐low carbon steel “0.02% C” till medium carbon steel grades “0.20% C.” Moreover, the work controls the steel melt tapping parameters for best cost achievement of steel melt yield and electrical energy consumption using simple measurements. These measurements are fitted into simple regression equations and contour plots for best refining stage control of the desired steel grade to be produced.

A review of simulation and numerical modeling of electric arc furnace (EAF) and its processes

“…This innovative approach enables the simultaneous execution of both smelting and refining operations within the furnace [ [85] , [86] ]. Elkoumy et at [ 87 ]. studied the empirical model for predicting process parameters during EAF refining stage based on real measurements.…”